Artificial Intellegence

One Week £ 1,900 | Two Week £3,500 | One Week ₦ 100,500


Artificial Intelligence was once exclusively the bastion of theoretical computer science. However, today, AI has stepped out of the ivory tower and is making inroads into the mainstream of Information systems technology in organisation. This seminar is designed to make the IT professional technologically aware of the areas of AI that are beginning to permeate mainstream systems. This high-level technology seminar will examine the state of AI in the IT marketplace and examine those areas that will have the greatest application for emerging technology.

This course has been created for managers, solutions architects, innovation officers, CTOs, software architects and everyone who is interested overview of applied artificial intelligence and the nearest forecast for its development.

  • Artificial Intelligence History
    • Introduction to Artificial Intelligent
    • Control, Planning and Scheduling
  • Problem Solving
    • Solving Problems by Searching
    • Beyond Classical Search
    • Adversarial Search
    • Constraint Satisfaction Problems
  • Knowledge and Reasoning
    • Logical Agents
    • First-Order Logic
    • Inference in First-Order Logic
    • Classical Planning
    • Planning and Acting in the Real World
    • Knowledge Representation
  • Knowledge representation, problem solving, and learning methods in solving
  • Learning
    • Learning from Examples
    • Knowledge in Learning
    • Learning Probabilistic Models
    • Reinforcement Learning
  • Communicating, Perceiving, and Acting
    • Natural Language Processing
    • Natural Language for Communication
    • Perception
    • Robotics

By the end of this workshop, participants will be able to

  • Explain the basic knowledge representation, problem solving, and learning methods of Artificial Intelligence
  • Assess the applicability, strengths, and weaknesses of the basic knowledge representation, problem solving, and learning methods in solving particular engineering problems
  • Develop intelligent systems by assembling solutions to concrete computational problems
  • Understand the role of knowledge representation, problem solving, and learning in intelligent-system engineering